Improving Ontology Matching Using Application Requirements for Segmenting Ontologies

Ontology matching is concerned with finding relations between elements of different ontologies. In large-scale settings, some significant challenges arise, such as how to achieve a reduction in the time it takes to perform matching and how to improve the quality of results. Current techniques involve the use of ontology segmentation to overcome having such a large number of elements to compare. However, current methods usually select the most relevant ontology elements based on the number of relationships, which may dismiss some elements should they have fewer or no relationships. Therefore, we propose an algorithm for ontology segmentation based on application requirements, in such a way that the users can specify the concepts that are the most relevant in their application context to generate the segments which will be used as an input for the matching. In the experiments, we found a general reduction in the execution time and some significant quality improvements, depending on what matcher is applied. In order to assess the proposed algorithm, we considered some well-known evaluation measures, such as precision, recall, and F-Measure

Towards Interoperable Research Infrastructures for Environmental and Earth Sciences

This open access book summarises the latest developments on data management in the EU H2020 ENVRIplus project, which brought together more than 20 environmental and Earth science research infrastructures into a single community. It provides readers with a systematic overview of the common challenges faced by research infrastructures and how a ‘reference model guided’ engineering approach can be used to achieve greater interoperability among such infrastructures in the environmental and earth sciences. The 20 contributions in this book are structured in 5 parts on the design, development, deployment, operation and use of research infrastructures. Part one provides an overview of the state of the art of research infrastructure and relevant e-Infrastructure technologies, part two discusses the reference model guided engineering approach, the third part presents the software and tools developed for common data management challenges, the fourth part demonstrates the software via several use cases, and the last part discusses the sustainability and future directions